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We present laboratory measurements of the chemical speciation of black carbon particles produced from burning a series of biomass fuels during FLAME III (2009). A soot particle aerosol mass spectrometer (SP-AMS) was utilized to study the chemical composition of refractory black carbon particles and the associated nonrefractory components. We examine the effect of source fuel and combustion efficiency on the chemical composition of the emitted black carbon aerosol particles. Fifteen different source fuel types were examined. Two distinct types of black carbon spectra were observed: Low mass to charge (C1 + -C5 + ) black carbon cluster ions were observed for all fuels while high mass to charge (>C32 + ) black carbon cluster ions with distinctive fullerene structure were found for turkey oak and pine species. The relative ratios between the mass concentrations of non-refractory organic species and black carbon varied between fuel types and displayed an inverse correlation with the modified combustion efficiency (MCE) of the burns. Finally, positive matrix factorization (PMF) was conducted on the SP-AMS mass spectra in order to examine the variability in the chemical composition of the observed biomass burning particles and to identify potential signatures of different fuel types. [ABSTRACT FROM AUTHOR]

The U. S. Environmental Protection Agency in collaboration with the U. S. Air Force Arnold Engineering Development Complex conducted the VAriable Response In Aircraft nvPM Testing (VARIAnT) 3 and 4 test campaigns to compare nonvolatile particulate matter (nvPM) emissions measurements from a variety of diffusion flame combustion aerosol sources (DFCASs), including a Cummins diesel engine, a diesel powered generator, two gas turbine start carts, a J85-GE-5 turbojet engine burning multiple fuels, and a Mini-CAST soot generator. The VARIAnT research program was devised to understand reported variability in the ARP6320A sampling system nvPM measurements. The VARIAnT research program has conducted four test campaigns to date with the VARIAnT 3 and 4 campaigns devoted to: (1) assessing the response of three different black carbon mass analyzers to particles of different size, morphology, and chemical composition; (2) characterizing the particles generated by 6 different combustion sources according to morphology, effective density, and chemical composition; and (3) assessing any significant difference between black carbon as determined by the 3 mass analyzers and the total PM determined via other techniques. Results from VARIAnT 3 and 4 campaigns revealed agreement of about 20% between the Micro-Soot Sensor, the Cavity Attenuated Phase Shift (CAPS PM SSA) monitor and the thermal-optical reference method for elemental carbon (EC) mass, independent of the calibration source used. For the LII-300, the measured mass concentrations in VARIAnT 3 fall within 18% and in VARIAnT 4 fall within 27% of the reference EC mass concentration when calibrated on a combustor rig in VARIAnT 3 and on an LGT-60 start cart in VARIAnT 4, respectively. It was also found that the three mass instrument types (MSS, CAPS PM SSA , and LII-300) can exhibit different BC to reference EC ratios depending on the emission source that appear to correlate to particle geometric mean mobility diameter, morphology, or some other parameter associated with particle geometric mean diameter (GMD) with the LII-300 showing a slightly stronger apparent trend with GMD. Systematic differences in LII-300 measured mass concentrations have been reduced by calibrating with a turbine combustion as a particle source (combustor or turbine engine). With respect to the particle size measurements, the sizing instruments (TSI SMPS, TSI EEPS, and Cambustion DMS 500) were found to be in general agreement in terms of size distributions and concentrations with some exceptions. Gravimetric measurements of the total aerosol mass produced by the various DFCAs differed from the reference EC, BC and integrated particle size distribution measured aerosol masses. The measurements of particle size distributions and single particle analysis performed using the miniSPLAT indicated the presence of larger particles (≳150 nm) having more compact morphologies, higher effective density, and a composition dominated by OC and containing ash. This increased large particle fraction is also associated with higher values of single scattering albedo measured by the CAPS PM SSA instrument and higher OC measurements. These measurements indicate gas turbine engine emissions can be a more heterogeneous mix of particle types beyond the original E−31 assumption that engine exit exhaust particles are mainly composed of black carbon. • PA and CAPS BC mass measurement methods have less variability than the LII BC method. • Gravimetric mass 30–40% greater than reference EC and 50–60% greater than BC masses. • Secondary particle mode >150 nm was observed dominated by non-volatile OC and containing ash. • Calibration of LII with a turbine combustion source more effective than other methods. [ABSTRACT FROM AUTHOR]

Abstract The composition and carbon nanostructure of soot are important parameters influencing health and climate effects, and the efficacy of soot mitigation technologies. We used laser-vaporization, electron-ionization aerosol mass spectrometry (or SP-AMS) to systematically investigate relationships between aerosol mass spectra, carbon nanostructure (HRTEM), and composition (thermal-optical carbon analysis) for soot with varying physicochemical properties. SP-AMS refractory black carbon concentrations (based on C ≤ 5 + clusters) were correlated to elemental carbon (r = 0.98, p < 10−8) and equivalent black carbon (aethalometer) concentrations. The SP-AMS large carbon ( C ≥ 6 + , midcarbons and fullerene carbons) fraction was inversely correlated to fringe length (r = −0.97, p = 0.028) and linearly correlated to the fraction of refractory organic carbon that partially pyrolize during heating (r = 0.89, p < 10−4). This refractory organic carbon material was incompletely detected with conventional aerosol mass spectrometry (flash vaporization at 600 °C). This suggests that (SP-AMS) refractory carbon cluster analysis provides insight to chemical bonding and nanostructures in refractory carbon materials, lowcarbons ( C ≤ 5 + ) indicate mature soot and large carbons indicate refractory organic carbon and amorphous nanostructures related to C 5 -components. These results have implications for assessments of soot particle mixing state and brown carbon absorption in the atmosphere and enable novel, on-line analysis of engineered carbon nanomaterials and soot characteristics relevant for climate and health. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

Abstract: A novel charge-based technique for classifying fractal-like aerosol agglomerates based on their morphology is demonstrated. The study discusses the application of this technique to flame soot aerosols where singly and doubly net-charged agglomerates of similar sizes were segregated using electrostatic classifiers and shown to have different morphologies. The flexibility and simplicity of this technique does not limit its application to aerosols, making it an attractive candidate for performing particle shape selection of different types of nano and micromaterials. [Copyright &y& Elsevier]

Abstract: We report the quantification of ambient particle-bound polycyclic aromatic hydrocarbons (PAHs) for the first time using a real-time aerosol mass spectrometer. These measurements were carried out during the Mexico City Metropolitan Area field study (MCMA-2003) that took place from March 29 to May 4, 2003. This was the first time that two different fast, real-time methods have been used to quantify PAHs alongside traditional filter-based measurements in an extended field campaign. This paper focuses on the technical aspects of PAH detection in ambient air with the Aerodyne AMS equipped with a quadrupole mass analyzer (Q-AMS), on the comparison of PAHs measured by the Q-AMS to those measured with the other two techniques, and on some features of the ambient results. PAHs are very resistant to fragmentation after ionization. Based on laboratory experiments with eight PAH standards, we show that their molecular ions, which for most particulate PAHs in ambient particles are larger than 200amu, are often the largest peak in their Q-AMS spectra. Q-AMS spectra of PAH are similar to those in the NIST database, albeit with more fragmentation. We have developed a subtraction method that allows the removal of the contribution from non-PAH organics to the ion signals of the PAHs in ambient data. We report the mass concentrations of all individual groups of PAHs with molecular weights of 202, 216, 226+228, 240+242, 250+252, 264+266, 276+278, 288+290, 300+302, 316 and 326+328, as well as their sum as the total PAH mass concentration. The time series of the Photoelectric Aerosol Sensor (PAS) and Q-AMS PAH measurements during MCMA-2003 are well correlated, with the smallest difference between measured PAH concentrations observed in the mornings when ambient aerosols loadings are dominated by fresh traffic emissions. The Q-AMS PAH measurements are also compared to those from GC–MS analysis of filter samples. Several groups of PAHs show agreement within the uncertainties, while the Q-AMS measurements are larger than the GC–MS ones for several others. In the ambient Q-AMS measurements the presence of ions tentatively attributed to cyclopenta[cd]pyrene and dicyclopentapyrenes causes signals at m/z 226 and 250, which are significantly stronger than the signals in GC–MS analysis of filter samples. This suggests that very labile, but likely toxic, PAHs were present in the MCMA atmosphere that decayed rapidly due to reaction during filter sampling, and this may explain at least some of the differences between the Q-AMS and GC–MS measurements. [Copyright &y& Elsevier]

A generalised method for the deconvolution of mass spectral data from the aerodyne aerosol mass spectrometer (AMS) is presented. In this instrument, the sampled ensemble of gas and non-refractory particle phase materials interfere with each other in the mass spectra and the data must be systematically analyzed to generate meaningful, quantitative and chemically resolved results. The method presented here is designed to arithmetically separate the raw data into partial mass spectra for distinct chemical species. This technique was developed as part of the AMS analysis tools introduced by Allan et al. (J. Geophys. Res. Atmos. 108 (2003) 4090) and is in use by most groups within the AMS users community. This technique employs a user-definable ‘fragmentation table’ for each chemical species or group of species, and examples of some tables designed for the interpretation of field data are given. The ongoing work being performed to develop and validate the tables will be presented in future publications. [Copyright &y& Elsevier]

Using data from ground-level measurements, this work evaluates the performance of one chemical transport model (CTM)-based approach using MERRA2 model output and one statistical approach using a generalized additive model to translate remotely-sensed Aerosol Optical Depth (AOD) measurements from the MODIS combined Deep Blue and Dark Target algorithm to surface-level PM 2.5 concentrations for nine cities in low and middle-income countries that include a range of environmental conditions (e.g. , mountainous, dusty, or coastal conditions) and only have between 1 and 10 ground level monitoring sites available. This evaluation shows that the CTM-based and statistical approaches tested here generally had a low correlation with the true daily-average PM 2.5 values within these nine cities, in contrast to previous studies that had showed stronger correlations over other regions. In addition, the uncertainty in the satellite-based estimates of the daily-average PM 2.5 concentration at a given location in a city tended to be very large (21–77% for the statistical methods, and 48–85% for the CTM-based methods). Many cities also had significant limitations in the availability of satellite observations of aerosols throughout the year due to their coastal location, persistent clouds, or persistent seasonal snow cover. The satellite-based methods tested in this work appear to work best for low altitude, inland cities like Hanoi and Delhi, but still have significant errors (43–60%) in predictions of daily-average PM 2.5 concentrations at sites within these cities. The CTM-based satellite approach tested here tended to underestimate PM 2.5 in high-altitude cities (except for Addis Ababa, Ethiopia, where they overestimate). However, this work suggests that under some conditions, adding satellite data to ground-level monitoring (GLM) network data via co-kriging may reduce the number of GLM sites needed to characterize PM 2.5 concentrations within a city, but this needs to be determined on a case-by-case basis. This evaluation is then used to make recommendations to countries with sparse GLM networks on how to incorporate the use of satellite observations in their PM 2.5 monitoring and under what conditions satellite approaches are likely to be unsuccessful. • The error in satellite-based estimates of the daily PM 2.5 concentration was 21–85%. • The tested cities had little AOD data due to coasts, clouds, or snow cover. • Satellite-based methods appear to work best for low altitude, inland cities. [ABSTRACT FROM AUTHOR]